Structure, Dynamics and Implied Gating Mechanism of a Human
Cyclic Nucleotide-Gated Channel
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Citation
Gofman, Yana, Charlotta Schärfe, Debora S. Marks, Turkan
Haliloglu, and Nir Ben-Tal. 2014. “Structure, Dynamics and
Implied Gating Mechanism of a Human Cyclic Nucleotide-Gated
Channel.” PLoS Computational Biology 10 (12): e1003976.
doi:10.1371/journal.pcbi.1003976.
http://dx.doi.org/10.1371/journal.pcbi.1003976.
Published Version
doi:10.1371/journal.pcbi.1003976
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June 14, 2017 9:15:37 AM EDT
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Structure, Dynamics and Implied Gating Mechanism of a
Human Cyclic Nucleotide-Gated Channel
Yana Gofman1¤, Charlotta Schärfe2,3, Debora S. Marks3, Turkan Haliloglu4, Nir Ben-Tal1*
1 Department of Biochemistry and Molecular Biology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv, Israel, 2 Center for Bioinformatics, Quantitative
Biology Center, and Department of Computer Science, Tübingen University, Tübingen, Germany, 3 Department of Systems Biology, Harvard University, Boston,
Massachusetts, United States of America, 4 Polymer Research Centre and Chemical Engineering Department, Bogazici University, Bebek-Istanbul, Turkey
Abstract
Cyclic nucleotide-gated (CNG) ion channels are nonselective cation channels, essential for visual and olfactory sensory
transduction. Although the channels include voltage-sensor domains (VSDs), their conductance is thought to be
independent of the membrane potential, and their gating regulated by cytosolic cyclic nucleotide–binding domains.
Mutations in these channels result in severe, degenerative retinal diseases, which remain untreatable. The lack of structural
information on CNG channels has prevented mechanistic understanding of disease-causing mutations, precluded structurebased drug design, and hampered in silico investigation of the gating mechanism. To address this, we built a 3D model of
the cone tetrameric CNG channel, based on homology to two distinct templates with known structures: the transmembrane
(TM) domain of a bacterial channel, and the cyclic nucleotide-binding domain of the mouse HCN2 channel. Since the TMdomain template had low sequence-similarity to the TM domains of the CNG channels, and to reconcile conflicts between
the two templates, we developed a novel, hybrid approach, combining homology modeling with evolutionary coupling
constraints. Next, we used elastic network analysis of the model structure to investigate global motions of the channel and
to elucidate its gating mechanism. We found the following: (i) In the main mode of motion, the TM and cytosolic domains
counter-rotated around the membrane normal. We related this motion to gating, a proposition that is supported by
previous experimental data, and by comparison to the known gating mechanism of the bacterial KirBac channel. (ii) The
VSDs could facilitate gating (supplementing the pore gate), explaining their presence in such ‘voltage-insensitive’ channels.
(iii) Our elastic network model analysis of the CNGA3 channel supports a modular model of allosteric gating, according to
which protein domains are quasi-independent: they can move independently, but are coupled to each other allosterically.
Citation: Gofman Y, Schärfe C, Marks DS, Haliloglu T, Ben-Tal N (2014) Structure, Dynamics and Implied Gating Mechanism of a Human Cyclic Nucleotide-Gated
Channel. PLoS Comput Biol 10(12): e1003976. doi:10.1371/journal.pcbi.1003976
Editor: Michael Nilges, Institut Pasteur, France
Received February 10, 2014; Accepted October 9, 2014; Published December 4, 2014
Copyright: ß 2014 Gofman et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the Israel Science Foundation (Grant 1331/11). TH’s research is supported by State Planning Organization (TÜBİTAK project
no: 110T088) and Betil Fund. TH and NBT acknowledge the support of the North Atlantic Treaty Organization (Traveling Grant ESP.CLG 984340). The funders had
no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* Email: [email protected]
¤ Current address: Department of Structural Biology, Stanford University, Stanford, California, United States of America
are composed of two CNGA3 and two CNGB3 subunits, with
alike subunits positioned next to each other [7] (see also a recent
work by Ding and colleagues suggesting a composition of three
CNGA3 subunits and one CNGB3 subunit in a cone channel [8]).
Binding of cyclic guanosine monophosphate (cGMP) to CNBD
controls the activity of the cone channels [1,3,6]. The cone system
confers color vision; about 70 mutations in the CNGA3 and
CNGB3 have been associated with achromatopsia, characterized
by color blindness, photophobia, nystagmus and impaired visual
acuity [3]. However, most of these mutations have been observed
only in isolated cases, and even among the more commonlyobserved mutations the precise mechanisms causing diseases are
unknown (Tables S1 and S2) [3,9], thus hindering drug-discovery
efforts. These challenges are further complicated by the poor
understanding of the gating mechanism of the CNG channel,
despite the available structural information on the membrane
domain of a bacterial homolog [10] and on the regulatory
cytosolic domain of both CNG and closely related hyperpolarization-activated cyclic nucleotide-gated (HCN) channels from
various organisms [11–20].
Introduction
Cyclic nucleotide-gated (CNG) ion channels are nonselective
cation channels, essential for visual and olfactory sensory
transduction in vertebrates [1–4]. Like other members of the
voltage-gated-like ion channel superfamily [2], the CNG channels
are composed of four (identical or similar) monomers, each
containing six transmembrane (TM) helices (referred to as S1–S6)
[1,3]. The first four TM helices in each monomer (S1–S4) form a
voltage-sensor domain (VSD); the last two helices (S5 and S6,
connected by the P-loop) of the four subunits assemble jointly to
form the central pore. In spite of the presence of the VSD, CNG
channels display very little voltage-dependent activity [1–4].
Rather, the channel is gated by cyclic nucleotide binding to a
cytosolic cyclic nucleotide–binding domain (CNBD), connected by
a so-called C-linker to the C-terminus of the S6 helix [1–4].
In vertebrates, the six known members of the CNG channel
family, classified into A and B subtypes, can coassemble in several
combinations to produce functional heterotetrameric channels [1–
6]. In cone photoreceptors, functional tetrameric CNG channels
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Structure, Dynamics and Gating of a Cyclic Nucleotide-Gated Channel
modeling process was complicated by the use of two distinct
templates, as well as by low sequence similarity between the
queries and the template for the TM domain, we also evaluated
the model structure using EVcouplings, a recently-developed
methodology that identifies evolutionarily coupled residues from
sequence variation data [30,31]. As evolutionarily coupled
residues often interact physically in the 3D space of a protein
[32], this and similar methods (reviewed in [33,34]) have been
successfully applied to predict structures of membrane and soluble
proteins, as well as to detect residues participating in conformational changes and protein-protein interactions. Here we used
evolutionary couplings (i) to evaluate our model structure of the
cone channel and (ii) to select the best conformations in ambiguous
regions of the model and in regions in which the two templates
yielded overlapping, conflicting predictions.
To analyze the channel dynamics, we used coarse-grained
elastic network models [35–37]. In the channel’s slowest,
dominant mode of motion, the TM and cytosolic domains rotate
around the membrane normal in opposite directions. We related
this mode of motion to gating, a proposition supported by
experimental evidence [38,39], as well as by comparison to the
gating mechanism of the bacterial KirBac channel. KirBac
channels resemble CNG channels in the architecture of the pore
domain and in the function of the cytoplasmic domain.
Additionally, investigation of the next-slowest modes of motion
revealed that the TM and the cytosolic domains fluctuate
alternatively in each mode, with cooperativity between the mobile
and immobile domains. This observation is consistent with the
modular gating model of the cone channel [28].
Author Summary
Cyclic nucleotide-gated (CNG) channels mediate the
passage of cations through the cytoplasmic membrane.
They are involved in sensory transduction and cellular
development in the rod and cone photoreceptors, as well
as in brain, kidney, heart and other cells, and are linked to
achromatopsia and other rare genetic diseases. We used a
hybrid modeling approach, combining comparative modeling and estimates of evolutionary conservation and
couplings, to model the structure of a human cone CNG
channel. The channel comprises a membrane domain that
allows ion passage, and a regulatory cytosolic domain that
binds cyclic nucleotides. The structure of each domain was
modeled by homology on the basis of a suitable template.
Our hybrid approach allowed us to evaluate the model
structure, as well as to determine the conformations of
regions where the templates overlapped and presented
conflicting structural evidence. We then conducted normal
mode analysis to reveal global motions of the channel. We
suggest that the main mode of motion, counter-rotation of
the membrane and cytosolic domains around the membrane normal, is associated with channel gating. Such
rotational motion induces minimal perturbation to the
lipid membrane, which could explain why the motion is
observed in other types of channels.
Several different models have been proposed to describe the
gating process of CNG channels (reviewed in [5,21–23]). The
models differ from one another in the minimum number of bound
nucleotides required for activation, the cooperativity among the
binding sites, and the number of open and closed states. The
simplest model, known as the sequential model, suggests that three
ligand molecules bind to the closed channel, and that the binding
of a fourth molecule causes the transition to the open state [24].
The sequential model does not account for the experimentally
confirmed opening of unliganded or partially-liganded CNG
channels and is therefore insufficient [25]. The classical Monod,
Wyman, and Changeux (MWC) model [26], initially aimed at
describing cooperative properties of bacterial regulatory enzymes
and hemoglobin, postulates that the channel can open with any
number of bound ligands, i.e., 0 to 4; the higher the number of
bound ligands, the more favorable the transition from the closed to
the open state [5]. Although the MWC model accurately describes
some features of CNG channels, it does not account for the
existence of sub-conductance states, allowing only one open state
[22]. A third model describes the tetramer as a dimer of dimers;
each dimer acts as an MWC unit, and the monomers within the
dimer display cooperativity [27]. In order for the channel to open,
both dimers must be activated independently (no cooperativity
between the dimers). The last model, the modular gating model,
defines modules within the channel: the VSD, the pore, the Clinker and the CNBD [28]. Each module can independently switch
between two possible conformations: the VSD and the C-linker
can be either resting or activated; the pore can be closed or open;
and the CNBD can be ligand-free (apo) or –bound (holo). Yet, the
modules are coupled to each other, so that the state of each
module can affect the states of other modules.
In order to elucidate the channel gating mechanism, we built
3D models of the tetrameric CNG channel in its resting state, with
the CNBDs in apo- and holo-conformations. We built the
homology model from two distinct templates—one corresponding
to the TM domain and the other corresponding to the cytosolic
domain—and evaluated the model structure on the basis of its
evolutionary conservation profile [29]. However, because the
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Results
The model structure displays typical conservation and
hydrophobicity profiles and is compatible with
experimental results in the homologous CNGA1 protein
We modeled by homology the 3D structure of the cone CNG
channel using two distinct templates: the TM region structure of
the bacterial channel MlotiK1, and the cytosolic domain structure
of the mouse HCN2 channel (Fig. 1). We projected ConSurf [40]
conservation scores of the CNGA3 and CNGB3 subunits,
composing the cone channel, onto the resultant model to evaluate
it (Fig. 2). The evolutionary conservation profile has previously
been demonstrated to be a valuable tool for assessing the quality of
model structures; the assessment approach is based on the
observation that the protein core is typically conserved, whereas
residues that face the surroundings, either lipids or water, are
variable [29]. Our model structure was compatible with the
anticipated evolutionary profile (Fig. 2). The model structure of
the TM domain was also compatible with the expected
hydrophobicity profile: hydrophobic residues were exposed to
the lipid, and charged and polar amino acids were buried in the
protein core or located in the loop regions (Figure S1). The model
correlates well with the experimental data available for the closely
homologous bovine channel CNGA1 (Text S1; Figures S2 and
S3). Furthermore, it suggests molecular interpretations for the
effects of known clinical mutations (Text S1; Tables S1 and S2;
Figure S4).
The model structure is mostly compatible with predicted
evolutionary couplings
We further evaluated the predicted model structure of the
CNGA3 monomer and tetramer using evolutionary couplings
calculated separately for the TM domain and for the cytosolic
domain. To this end, we used the EVcouplings algorithm [30,31].
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Structure, Dynamics and Gating of a Cyclic Nucleotide-Gated Channel
domains, 75% and 92%, respectively, were in contact. A control
calculation using the templates revealed similar ratios of contacting
evolutionary couplings in the two domains (Figure S5). A more
detailed analysis of the couplings detected between residues that
were not in contact according to the model structure (or the
templates) suggested that most of these are related to flexibility in
the loop regions (Text S1).
Evolutionary couplings support the model structure in
regions with conflicting structural data
Overall, our model structure was compatible with the anticipated hydrophobicity (Figure S1) and evolutionary (Fig. 2)
patterns, as well as with mappings of evolutionary couplings
(Fig. 3). However, we considered alternative conformations for
two specific regions in the model, i.e., helix S1 of the TM domain
(Figure S6) and the S6-C-linker interface of the cytosolic domain
(Fig. 1). First, secondary structure prediction methods (Figures
S6A and S6B), in addition to the hydrophobicity profile of the
homologs in the region (Figure S6D), pointed to two main
alternatives for the boundaries of helix S1: 170–186, used in the
original model, vs. 174–190 (Figure S6D). Second, for the region
connecting helix S6 and the C-linker, either of the two templates
could have been used (i.e., either the TM domain of bacterial
MlotiK1 channel or the cytosolic domain of the mouse HCN2
channel), and we based our model structure on the mammalian
template. However, we considered an alternative model structure,
in which the conformation of this region was based on the
bacterial template (Figs. 1A and 1B). Overall, we constructed two
alternative model structures of the CNG channel (in addition to
the original): one with different boundaries for the S1 helix, and
another one with a different conformation of the S6-C-linker
interface. We correlated the overlay of the contacts in these models
with the evolutionary couplings and concluded that the original
model agrees with the data better than either alternative (Fig. 3,
the insets).
Figure 1. Modeling of the full-length cone channel in its resting
state, on the basis of two separate templates. (A) Side view of the
TM region of the bacterial channel MlotiK1 in a closed state, PDB entry
3BEH [10]. This structure was the template for modeling the TM region
of the cone channel. (B) Side view of the mouse HCN2 CNBDs in a
resting state, PDB entry 1Q3E [15]. This structure served as a template
for the cytosolic domain of the cone channel. (A, B) The regions of
conflict between the templates are in red. (C) Side view of the resultant
model structure of the human cone channel, shown in cartoon
representation. CNGA3 subunits are colored cyan (light and dark);
CNGB3 subunits are colored orange (light and dark).
doi:10.1371/journal.pcbi.1003976.g001
For each domain we carried out the comparison using the 2L/3
residues with the greatest coupling strength, where L is the
sequence length; L = 240 in the TM region and L = 197 in the
cytoplasmic region; see Methods. In both domains the overlay of
the calculated evolutionary couplings and the contacts derived
from the model structure was remarkable (Fig. 3): among the
residue pairs used in the evaluations of the TM and cytosolic
Figure 2. The evolutionary conservation profile supports the model structure. The channel is colored by conservation grades according to the
color-coding bar, with variable-through-conserved corresponding to turquoise-through-maroon. Overall, the variable residues are peripheral,
whereas the conserved residues are in the structural core and channel pore. (A) Side view of the model structure in cartoon representation; the
CNBDs are in their holo-state. (B) Extracellular view of the TM domain of the model structure. The proposed locations of the two CNGA3 and two
CNGB3 subunits are marked [7].
doi:10.1371/journal.pcbi.1003976.g002
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Structure, Dynamics and Gating of a Cyclic Nucleotide-Gated Channel
Figure 3. Evolutionary coupling (EC) calculations support the model. Contact maps of top-ranked predicted ECs (red) overlaid on monomer
(light grey) and intermonomer (dark grey) contacts from (A) the model structure of the TM domain of CNGA3; (B) the model structure of the cytosolic
domain of CNGA3. The insets show the contact maps of alternative CNGA3 model structures; the orange arrows point to evolutionary couplings
between amino acid pairs that are not in contact in the alternative models, but are in contact in our final model. Clearly, the overlay of the ECs with
the contact map is far better for the chosen model structure than for the alternatives.
doi:10.1371/journal.pcbi.1003976.g003
state of each module affects the states of other modules, i.e., quasiindependent dynamic units [28].
In order to examine the effect of the VSDs on channel
dynamics, we performed elastic networks analysis of a variant of
the channel in which the VSDs were removed (Figure S8). The
dynamics remained, in essence, the same, aside from the motions
that directly involve the VSDs.
Equilibrium dynamics of the CNGA3 channel
We used coarse-grained elastic network models to investigate
global motions of the cone channel. We chose this methodology
because it is insensitive to the atomic details of the (imprecise)
model structure and is capable of exploring large-scale motions,
related to channel gating and inactivation [37,41]. For simplicity
and to facilitate more convenient representation of the data, we
focused on a symmetric tetrameric channel composed of four
identical CNGA3 subunits. The results obtained for the structure,
modeled based on CNBD templates in their apo- and holo-states,
were, in essence, identical, and thus we only describe the results
obtained for the apo-state.
A complete description of the results is provided in Text S1.
Briefly, the channel dynamics are dominated by three types of
motion. In motion I the channel is divided into two dynamic units:
the TM domain and the cytosolic domain (Fig. 4A). The two
domains rotate around the membrane normal in opposite
directions (Fig. 4B). In motion II the VSDs are swinging, while
the pore domain, as well as the C-linkers and the CNBDs, are
essentially stationary (Fig. 4D and Figure S7B). The fluctuations of
the VSDs are positively correlated with those of the C-linker and
the CNBD of the same subunit, and with those of the pore region
of the adjacent subunit (Fig. 4C). In motion III the pairs of
diagonal CNBDs alternately move towards and away from each
other (Fig. 4F). The fluctuations of the VSDs are positively
correlated with those of the CNBD, C-linker and pore region of
the adjacent subunits (Fig. 4E).
The analysis also shows that, in essence, all the motions, except
motion I, can be categorized into modes in which only the TM
domain is fluctuating (as in motion II) or modes in which only the
cytosolic domain fluctuates (as in motion III). Thus, each domain
is mobile individually. However, there is cooperativity between the
domains, which suggests that they affect each other (Figs. 4C and
4E). This observation corroborates the modular gating model of
the CNG channels, which postulates that the domains (modules)
can undergo conformational changes individually, but that the
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Discussion
We presented a model structure of a human CNG channel,
built using a unique computational protocol that includes
homology modeling, as well as evolutionary data from conservation and couplings analysis. The model correlates well with
mutagenesis and clinical data. Elastic network analyses of the
model-structure enable us to provide concrete suggestions
concerning the gating mechanism.
Rotational motion and gating
Motion I of the CNGA3 channel is a rotational, iris-like opening
(Figs. 4A and 4B). This motion is unique in that it is associated
with the only (non-degenerate) slow mode that manifests
cooperativity among all subunits and allows symmetry-preserving
conformational transition. Here we compare this motion with the
gating motion in KirBac channels, prokaryotic homologs of
mammalian inwardly rectifying potassium channels. KirBac
channels share the architecture of the pore domain with other
members of the voltage-gated-like ion channel superfamily, but
they lack the VSD. Similarly to CNG channels, KirBac channels
feature a cytoplasmic regulatory domain [42]. Recent crystal
structures of the KirBac3.1 channel in the open and closed states
(Fig. 5A) revealed its gating mechanism: upon activation, the TM
and cytoplasmic domains of KirBac3.1 rotate in opposite
directions around the membrane normal [43,44]. For comparison,
we performed elastic network analysis of the KirBac3.1 channel in
its closed state.
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Structure, Dynamics and Gating of a Cyclic Nucleotide-Gated Channel
Figure 5. Motion I of CNGA3 appears to describe channel gating.
For clarity, only helices S5 and S6 (or corresponding KirBac helices) of
two juxtaposed subunits are shown in each panel. (A, B) The similarity
between the predicted conformations in panel B and the crystal
structures in panel A is apparent, verifying the relation between these
conformations and channel gating. (A) Side view of the KirBac3.1 crystal
structures in open (pale green, PDB entry 3ZRS [43]) and closed (pale
red, PDB entry 2WLJ [44]) states. The a-carbons of the two gateresidues, namely G120 and Y132, are shown as a space-filling model. (B–
D) The edge conformations of KirBac3.1 (B), CNGA3 (C) and CNGA3
lacking the VSDs (D), as predicted by the elastic network models in the
slowest mode of motion. The two edge conformations are shown in red
and green. (C) The CNGA3 conformations resemble the conformations
predicted for the KirBac channel (panel B), but the pore region is rigid.
(D) The CNGA3 without VSD conformations are identical to the KirBac
conformations (panel B).
doi:10.1371/journal.pcbi.1003976.g005
Figure 4. The three principal motions. The cross-correlations between
the residues in each motion type are shown on the left panels (A, C, E);
the channel is colored according to the correlation of the VSD of chain
A with the other residues. The corresponding motions are presented on
the right panels (B, D, F). Snapshots are colored according to the
direction of motion, ranging from green to red. (A, C, E) In each panel,
chain A represents an arbitrary CNGA3 chain (the channel comprises
four identical chains). The magnitude of positive and negative
correlations between the fluctuations of the residues is color-coded
according to the blue-to-red scale at the bottom of the picture. Positive
correlation indicates motion of two residues in the same direction,
while negative correlation indicates motion in opposite directions. In
panel A, the arrows indicate the location of the pivot points of the
rotational motion at the termini of the S6 helices, i.e., the border
between the dynamics units (See Discussion). The CNBDs in panel D
and the TM domain in panel F are omitted for clarity.
doi:10.1371/journal.pcbi.1003976.g004
the TM domain (and the joint clockwise rotation of the
cytoplasmic domain) leads to pore opening (Figure S9).
The idea of a rotational motion related to the gating of CNG
channels is not new [38,39]. Based on existing experimental
evidence, Flynn and colleagues have associated a clockwise
rotation of the C-linkers with channel gating (reviewed in [39]).
The authors also indicated that a rotational gating motion requires
definition of a ‘pivot point’, the residues on the two sides of which
rotate in opposite directions. They proposed that in CNG
channels the pivot point is located at the top of the S6 helices.
Indeed, our elastic network analysis shows clockwise rotation of
the cytosolic domain, which is coupled to counterclockwise
rotation of the TM domain (Fig. 4A), an observation compatible
with their proposition and with the gating mechanism of the
KirBac channels [43]. However, our analysis indicates that the
pivot point is located at the C-termini (rather than the top) of the
S6 helices (Fig. 4A); it corresponds to the hinge in motion I around
residues 401–407 (Figure S7A).
Although CNG and KirBac channels display similar rotational
motion upon gating, there is an important difference between the
The slowest mode of motion of the KirBac3.1 channel displayed
rotational movement of the TM and cytoplasmic domains, which
resembled the shift between the open and closed states captured in
the crystal structures, i.e., the conformational change that occurs
upon gating (Figs. 5A and 5B) [43]. Because of the analogy
between this motion and motion I of the CNG channel, we
associate the latter motion with gating as well (Fig. 5). Indeed,
calculations using the edge conformations of the motion and the
HOLE software [45] show that the counter-clockwise rotation of
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Structure, Dynamics and Gating of a Cyclic Nucleotide-Gated Channel
topology [37,41]. In addition, elastic network models are capable
of capturing large-scale conformational changes, including changes that are dependent on external stimuli, such as voltage or ligand
binding. This is because the intrinsic modes of motion of a protein
are determined by its architecture only, and the elastic network
models can predict these modes solely from the structure,
regardless of the environment (water or membrane) [37]. Whereas
the environment can have an impact on the magnitude of the
global motions and on local interactions, it does not usually
determine their direction and nature [37]. Indeed, in previous
studies, slow modes of motion have been shown to describe
functional conformational changes in proteins, including membrane channels and transporters [35–37,41]. Finally, the strongest
support for the suitability of elastic network models as an approach
for detecting functionally important motions in CNG channels
comes from calculations we conducted with the KirBac3.1
channel: The dominant motions we detected for the CNG
channels were very similar to motions calculated for the KirBac3.1
channel, inferred to correspond to gating motions, according to
the known crystal structures of the channel in the open and closed
states (Fig. 5).
Evolutionary couplings have been successfully used to predict
the structures of membrane and soluble proteins (reviewed in
[33,34]), but our preliminary attempt to predict the structure of
the CNG channel using evolutionary couplings alone was
unsuccessful. This is perhaps because of the large number of
inter-subunit contacts in the unique architecture of the tetrameric
CNG channel; it is difficult to discriminate between couplings
associated with the intra- and inter-subunit contacts. Instead, we
used homology modeling to derive our model structure, and relied
on evolutionary couplings to validate the model and to distinguish
between possible conformations in regions of conflicting structural
evidence. This is somewhat related to the approach used in
reference [58].
In some cases, evolutionary couplings may reflect protein
conformational changes, as demonstrated for several TM transporters [30]. However, our evolutionary couplings map provided
no clues as to the channel’s conformational changes. We suggest
that the reason is that, in contrast to the major conformational
changes observed in transporters, conformational changes in
channels, including the rotational motion described above, are
minor and have little effect on residue contacts.
While this paper was in review, a homology model of the TM
domain of the canine CNGA3 channel was published [59]. The
model, obtained based on a chimeric Kv1.2/2.1 structural
template, corresponds to an open state of the channel, while our
model structure represents a closed conformation. The models are
based on different templates, and they also differ from each other
in the boundaries of the TM helices (Figure S6A); most differences
could perhaps be attributed to the conformational changes upon
channel opening/closure.
two channels. KirBac channels contain two activation gates: one in
the center of the S6 helix (near the P-loop) and one at the Ctermini of the S6 helices (Fig. 5A) [43]. In contrast, CNG channels
contain only a single gate, which is located in the pore region
[21,39]. We propose that in the absence of a second gate in the
CNG channels, the VSD provides an additional means of gating
regulation. Our conclusion derives from a close investigation of
rotational motion I of the CNGA3 channel in the presence
(Fig. 5C) and absence (Fig. 5D) of the VSDs. In the presence of
the VSDs (Fig. 5C), the fluctuations of the N-termini of the S6
helices are smaller in magnitude than they are in the absence of
these domains (Fig. 5D). In other words, the VSD stiffens the pore
region, so that the fluctuations in the gate region are limited. This
could explain why KirBac channels, lacking the VSD, have an
extra gate at the C-termini of the S6 helices [43], whereas CNG
channels, which do contain the VSD, have only one gate.
The idea that rotational motion can facilitate gating has been
proposed for other ion channels from various families, both
voltage-dependent and -independent [46–52]. This motion
appears to have minimal effect on the channel-membrane
interface, and causes minimal perturbation of the lipid membrane.
Thus, it is possible that many more ion channels share a similar
rotational gating mechanism.
Limitations of the study
The approach used to predict the structure of the cone channel
has certain drawbacks. First, the TM region was derived from the
structure of a distant homolog, with ,10% sequence identity
between query and template. This may have led to inaccuracies in
the model structure due to errors in the alignment of the query and
template sequences, as well as structural changes along the course
of evolution. However, the compatibility of the model structure
with the expected evolutionary and hydrophobicity patterns,
evolutionary couplings and the available experimental data is
encouraging (Figs. 2, 3 and Figures S1-S3). Second, our model
structure of the cone channel was derived from two distinct
templates. Therefore, the interface connecting these templates in
the model, i.e., the S6-C-linker region, might be inaccurate.
However, we have explored alternative conformations of the
region, and the evolutionary couplings agreed best with our model
structure (Fig. 3B). Third, the loop regions in any model structure
are expected to be imprecise [53]. Reassuringly, the exact loop
conformation that was chosen had little effect on the results of our
elastic network analysis. The fact that the results are insensitive to
minor structural changes suggests that other channels of the CNG
family might share dynamics similar to those of CNGA3. Lastly,
the fact that the cytosolic domain was modeled on the basis of the
crystal structure of the corresponding domain of an HCN channel
could also be problematic, as the resemblance of the CNG and the
HCN channels in this region has previously been called into
question, owing to conflicting experimental evidence [54]. That
the evolutionary couplings in the cytosolic domain of the human
CNGA3 channel and mouse HCN2 channel displayed similar
patterns suggests that they do share the same conformation in this
region (Fig. 3B and Figure S5B).
Given the weaknesses of the presented model structure, it is
quite natural to study the channel dynamics using elastic network
analysis, an approach that relies on a simplified representation of
the channel structure, comprising a-carbons connected by
Hookean springs of identical force constant [35,55–57]. That is,
the network models do not depend on the identity of the amino
acids and the specificity of interactions between them. Moreover,
the coarse-grained network models do not depend on the atomic
details of the structure and can tolerate some variations in
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Conclusions
We presented a 3D model structure of the heterotetrameric
human cone channel, composed of CNGA3 and CNGB3
subunits, performed elastic network model analysis of the
(equivalent homotetrameric CNGA3) channel, and obtained a
mechanistic view of its gating. The following are three ‘take-home
messages’:
1. We suggest that the slowest mode of motion, describing
counter-rotations of the TM and cytosolic domains around the
membrane normal, depicts channel gating. A similar gating
mechanism has been proposed for other ion channels.
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Structure, Dynamics and Gating of a Cyclic Nucleotide-Gated Channel
sequence alignment of 101 homologs that included the sequences
of the queries and the template. To this end, we searched for
MlotK1 homologs in the SwissProt database [68] using CSBLAST [69]; 3 iterations were performed with maximal e-value of
10-5. The collected homologs were aligned using the MUSCLE
program [62]. The final alignment between the queries and
template took into account the outputs of all methodologies used
(Figure S6). For the most part, in spite of the high sequence
diversity, there was consensus in the hydrophobicity profiles of the
homologs in the TM helices (e.g., Figure S6E), excluding S1.
Because of the observed deviations in the predicted boundaries of
the S1 segment, as well as the diversity of the hydrophobicity
profiles of the homologs in the region, we considered also an
alternative location of S1 in the sequence (Figure S6). Compared
with this alternative, the final model was in better agreement with
the evolutionary and hydrophobicity profiles, and with the
evolutionary couplings. Nevertheless, our confidence regarding
the boundaries of the S1 segment is lower compared with the other
TM segments.
The templates for the TM (PDB entry 3BEH) and cytosolic
domains (PDB entry 1Q3E) contain overlapping regions i.e.,
regions corresponding to the same amino acid segment in the
queries: residues 217–223 of PDB entry 3BEH and residues 443–
449 of PDB entry 1Q3E, corresponding to residues 407–413 in
CNGA3 and residues 449–455 in CNGB3. This region corresponds to the interface between the S6 helix in the TM domain
and the C-linker, and its orientation differs greatly between the
templates (Fig. 1). As bacterial cytosolic domains do not include Clinkers [11], we chose to model the region of conflict according to
the template of mammalian origin, i.e., PDB entry 1Q3E, covering
the cytosolic domain. The initial 3D models of the CNGA3 and
CNGB3 subunits were constructed using version v9.10 of the
MODELLER software [70].
Long loops, i.e., the loops connecting S1–S2, S2–S3 and S5-Ploop, were refined with the Rosetta loop modeling application
[71,72]. Rosetta created 1,000 decoys for each loop. The decoys
were then evaluated using the ConQuass method [29]. ConQuass
is based on the anticipation that evolutionarily conserved amino
acids are buried in the protein and that variable residues are
exposed to the environment, and assigns scores to the decoys based
on the degree to which they adhere to this pattern. In each of the
three refined loops the decoy with the best ConQuass score was
chosen for the final model. Evolutionary conservation profiles were
calculated as described below.
For comparison, we also constructed a model structure of the
CNG channel in which the S6-C-linker interface was modeled
according to the bacterial template, i.e., PDB entry 3BEH,
covering the TM domain. Overall, we constructed two alternative
model structures of the CNG channel (in addition to the original):
one with different boundaries of the S1 helix, and another one
with a different conformation of the S6-C-linker interface.
2. The presence of the VSD in the voltage-insensitive CNG
channels is a long-standing conundrum [10]. Recently, it was
shown that the domain affects trafficking [60], but one could
argue that from a parsimonious point of view it seems unlikely
that a whole domain would be preserved in evolution in a case
where a short peptide would do. Locations of high-frequency
disease-associated mutations (Text S1 ‘‘Mapping diseasecausing mutations on the model structure’’) and normal mode
calculations together suggest that the VSDs may also play a
role in gating, supplementing the pore gate.
3. Among the allosteric models of gating in CNG channels, the
elastic network model analysis of the CNGA3 channel supports
the modular gating variant. According to this model,
autonomous domains that can move independently are
coupled to each other such that conformational changes in
one may allosterically propagate within the tetrameric channel
structure [5,28].
Methods
Modeling of the CNGA3 and CNGB3 subunits
A CNG channel subunit consists of a TM domain and a
cytosolic domain comprising a CNBD and a C-linker. In the
absence of a high-resolution structure of an intact subunit, we
modeled the cone channel on the basis of existing structures
corresponding to the individual domains. CNG and HCN
channels are closely related in structure [5]; thus, HCN structures
can serve as templates for modeling CNGs. A variety of highresolution structures of mammalian cytosolic domains from HCN
channels are available [15–20]. As a template for the apo-state, we
used the mouse HCN2 channel (Protein Data Bank (PDB) entry
3FFQ [18]), the only available structure of a mammal cytosolic
domain in an apo-state. As a template for the holo-state, we used
the mouse HCN2 channel (PDB entry 1Q3E [15]), the only
available structure of the cytosolic domain in complex with cGMP.
Pairwise alignments between the queries and templates were
needed for the modeling. The CNBD of the mouse HCN2
channel shares sequence identities of 33% and 29% with the
cytosolic domains of CNGA3 and of CNGB3, respectively. When
a query and a template display sequence identity of 30% or more,
a model structure can be constructed on the basis of a simple
pairwise alignment [53]. Still, extraction of the pairwise alignment
from a multiple-sequence alignment can improve the model
accuracy [53]. We searched for the homologs of the mouse HCN2
channel in the CleanUniProt database [61] and aligned their
sequences using the MUSCLE program [62]. Both subunits,
CNGA3 and CNGB3, were detected as homologs, and their
alignments with the sequence of the mouse HCN2 channel were
extracted from the multiple sequence alignment (Figure S10).
The crystal structure of the bacterial MlotiK1 channel in its
closed state (PDB entry 3BEH [10]) served as a template for
modeling the TM domains of CNGA3 and CNGB3. The
sequence identities between the TM domain of MlotK1 and those
of CNGA3 and CNGB3 were only 10% and 12.5%, respectively.
Thus, aligning both queries to the template was challenging. In
cases of such low query-template similarity it is recommended to
use a variety of tools in order to produce a reliable pairwise
alignment [53]. We exploited the secondary structure prediction
algorithm PsiPred [63], several methods for the identification of
TM segments, namely MEMSAT [64] and HMMTOP [65], a
methodology for profile-to-profile alignment HHpred [66], and
the FFAS03 server [67] for both profile-to-profile alignment and
fold-recognition (Figure S6). Additionally, we created a multiple
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Calculation of ConSurf conservation profile
We used CS-BLAST [69] to collect homologous sequences of
CNGA3 and of CNGB3 from the CleanUniProt database [61].
Redundant (.99% sequence identity) and fragmented sequences
were discarded. We aligned the sequences (183 and 223 amino
acids for CNGA3 and CNGB3, respectively) using the MUSCLE
program [62] and then calculated the conservation profiles using
the ConSurf web-server [40].
Calculation of evolutionary couplings
A reliable calculation of evolutionary couplings requires a
particularly large collection of homologous sequences [33]. We
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Structure, Dynamics and Gating of a Cyclic Nucleotide-Gated Channel
where uk and lk are, respectively, the k-th eigenvector and k-th
eigenvalue of C, kB is the Boltzmann constant, and T is the
absolute temperature; kBT/c was taken as 1 Å2. The summation is
performed over all (k = 1 to N-1) non-zero eigenvalues. Overall,
Eq. 1 predicts the mean-square displacement of each residue
(node) when i = j, and when i ? j it predicts the correlations
between the fluctuations of residues i and j as a superimposition of
N-1 eigenmodes. lk is proportional to the k-th mode frequency,
the inverse of which gives the relative contribution of this mode to
the protein’s overall structural motion. The minima in the
obtained fluctuation profile for a given mode suggest possible
hinge points that coordinate the cooperative motions between
mobile structural elements in this mode.
In contrast to isotropic GNM, ANM determines the direction of
fluctuations. Here C is replaced by the 3N63N Hessian matrix H,
the elements of which are the second derivatives of the inter-node
potential described by Eq. 1, with a (commonly used) cutoff of
15 Å. The first 6 modes are zero eigenmodes, corresponding to the
rigid-body rotations and translations of the protein [37], and the
correlation between DRi and DRj is decomposed into 3N-6 modes
and calculated as follows:
failed to find a sufficient number of CNGA3 homologs that
included both the TM and CNB domains, and conducted
evolutionary couplings calculations for each domain separately.
Namely, we built a multiple sequence alignment for the TM
domain, i.e., residues 161–410, and another alignment for the Clinker with the CNBD, i.e., residues 410–610. To this effect, we
used the JackHMMer software [73] (5 iterations) to search for
similar sequences against the Uniprot database [74] using the
range 10215–10220 of e-values. These e-values yielded the largest
numbers of aligned sequences while maintaining coverage of the
input sequence. The final alignments covering the TM and
cytosolic domains contained 6,439 and 7,203 sequences, respectively. Although proteins from families such as voltage-gated
potassium channels can be aligned to the CNG channels at a high
e-value threshold, these families were excluded, as they introduced
many insertions and deletions. Importantly, this means that strong
evolutionary couplings deduced from alignment of the VSD
domain are not a consequence of inclusion of these known voltagegated channels. Redundant (.90% sequence identity) and
fragmented sequences were discarded. Evolutionary couplings
were then calculated using the EVcouplings webserver (www.
evfold.org) as described previously [31,33]; covariation information was inferred using the plmDCA algorithm (pseudolikelihood
maximization for Potts models with direct coupling analysis) [75].
All columns in the alignments containing gaps of less than 80%
were considered informative for the calculation. The evolutionary
couplings were ranked according to their coupling strength; for
each domain, we took the top 2/3 L strongest evolutionary
couplings (L = sequence length; L = 240 in the TM domain and
L = 197 in the cytoplasmic domain) and correlated them to the
contacts in the CNGA3 model structure.
For comparison, we also calculated evolutionary couplings for
the template sequences of the bacterial MlotiK1 and mouse
HCN2 using the same protocol. We compared the results to the
contact maps deduced from the crystal structures using distance
cutoffs between 10 and 15 Å; residue pairs with a-carbons below
the cutoff were considered in contact. The results were qualitatively the same for all cutoff points selected. In our analysis of the
model structure, we used the results based on a distance cutoff of
12 Å, reproducing over 95% of the detected evolutionary
couplings.
X T
SDRi DRj T~ð3kB T=cÞtr H {1 ij ~ð3kB T=cÞ k tr l{1
k uk uk ij
ð2Þ
where tr[H-1]ij is the trace of the ij-th submatrix [H21]ij of H21.
The summation is performed over all (k = 1 to 3N - 6) non-zero
eigenvalues. The eigenvectors allow us to identify alternative
conformations sampled by the individual modes, simply by
adding/subtracting the eigenvectors to/from the equilibrium
position in the respective modes. Thus, being an anisotropic
model, ANM provides information on the directions of the
motions in 3D, while GNM is more realistic with respect to the
mean-square fluctuations and the correlations between fluctuations [37].
Several studies have demonstrated that the first few slowest
GNM modes are implicated in protein function [36,37]. Therefore, we focused on the six GNM modes identified as slowest on
the basis of the distribution of the eigenvalues; these modes were
responsible for approximately 40% of the overall motion of the
channel (Figure S11). The superimposition of the residues’ meansquare displacement predicted by GNM and ANM revealed the
correspondence between the two elastic network models. Thus,
using ANM, we were able to determine the direction of
fluctuations characterized by GNM.
Elastic network models
We analyzed the model structure of the homotetrameric
CNGA3 channel using two elastic network models, namely, the
Gaussian network model (GNM) and the anisotropic network
model (ANM). We focused on the homotetrameric channel for
simplicity. The methodology of both elastic network models has
been described previously [35,55–57]; here we give a short
summary.
GNM calculations use a simplified representation of the protein,
in which the structure is reduced to a-carbon atoms and is treated
as an elastic network of nodes connected by hookean springs of
uniform force constant c. Two nodes i and j are assumed to display
Gaussian fluctuations around their equilibrium positions if the
distance between them is below the (commonly used) cutoff of
10 Å. The inter-node contacts are then defined by an N6N
Kirchhoff matrix C, where N is the number of amino acids in the
protein. The correlation between the fluctuations of two nodes i
and j, DRi and DRj, respectively, are calculated as follows:
Supporting Information
Text S1 The file contains the following sections: ‘‘Model
structure is compatible with experimental data available for the
homologous CNGA1 protein’’, ‘‘Mapping disease-causing mutations on the model structure’’, ‘‘Evolutionary couplings between
amino acids that are not in contact in the model structure’’,
‘‘Equilibrium dynamics of the CNGA3 channel’’ and ‘‘Supplementary references’’.
(PDF)
Figure S1 The hydrophobicity pattern of the model structure of
the TM domain of the human cone channel from side (A) and
extracellular (B) views. The model structure is colored according to
the color-coding bar, with blue-through-yellow corresponding to
hydrophilic-through-hydrophobic amino acids according to the
Kessel/Ben-Tal hydrophobicity scale [76]. The structure displays
a typical hydrophobicity pattern, with hydrophobic residues
X T
SDRi DRj T~ð3kB T=cÞ C {1 ij ~ð3kB T=cÞ k l{1
k uk uk ij ð1Þ
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Structure, Dynamics and Gating of a Cyclic Nucleotide-Gated Channel
exposed to the lipid, and charged and polar amino acids buried in
the protein core or located in the extramembrane regions.
(TIF)
the interface of the VSD with the p-loop. Replacement of L186
with a bulky Phe can interrupt the tight interface. (F) The effect of
the CNGB3 S435F mutation. An intracellular view of the pore
region of the cone channel is presented. S435 faces the central
pore, and its replacement with a bulky Phe can disrupt the helix
bundle and/or block the pore.
(TIF)
Figure S2 The model structure of the TM domain of the human
cone channel is in agreement with experimental data. (A)
Intracellular view of the pore region of the channel in cartoon
representation. The channel is colored grey. S6 residues accessible
to the central pore are colored green; S6 residues with
intermediate accessibility are colored yellow; S6 residues not
accessible to the central pore are colored red [77,78]. (B)
Extracellular view of the pore region of the cone channel in
cartoon representation. The CNGA3 subunits are colored cyan
(light and dark), and the CNGB3 subunits are colored orange (light
and dark); the a-carbons of CNGA3 L361 and F385 and the
corresponding CNGB3 R403 and F427 are shown as space-filled
atoms. The distance between the a-carbons of residues in the same
subunit, e.g., the distance between the a-carbons of L361 and
F385 in the CNGA3 subunit, was 10 Å (marked by a black line in
one of the subunits); the distance between the a-carbons of the
residues in neighboring subunits, e.g., the distance between the acarbons of CNGA3 F385 and CNGB3 R403, was 7 Å (marked by
a blue line in one of the subunits). It is apparent that the residues
can interact with each other [79].
(TIF)
Contact maps of top-ranked predicted evolutionary
couplings (ECs; red) overlaid on monomer (light grey) and
intermonomer (dark grey) contacts from (A) the crystal structure
of the bacterial MlotiK1 channel (TM domain); (B) the crystal
structure of the mouse HCN2 channel (cytosolic domain). The
blue and green lines show the location of a-helices and b-sheets in
the sequence, respectively.
(TIF)
Figure S5
Figure S6 Detecting the TM helices of human CNGA3 (A) and
CNGB3 (B) subunits. The locations of the TM helices according to
secondary-structure prediction (PsiPred [63]), TM segment
identification (MEMSAT [64] and HMMTOP [65]), profile-toprofile alignment (HHpred [66]) and fold recognition (FFAS03
[67]) are marked in different colors according to the legend. The
boundaries of the TM helices that were used for the modeling are
highlighted in yellow; the designation of TM helices is also marked
and highlighted in yellow. The black dashed line shows the
alternative location of helix S1. In (A) the grey lines show the
corresponding boundaries of TM helices derived from the recent
model-structure of the canine CNGA3 channel in open conformation [59]; some of the differences could be associated the
conformational changes upon channel opening/closure. (C) The
sequence alignment of the MlotK1, CNGA3 and CNGB3
channels used here for modeling the TM region. (D, E)
Hydrophobicity profiles of the S1 (D) and S3 (E) regions among
selected CNGA3 homologs. The sequences are colored according
to the color-coding bar, with blue-through-yellow corresponding
to hydrophilic-through-hydrophobic amino acids according to the
Kessel/Ben-Tal hydrophobicity scale [76]. (D) Defining the
boundaries of the S1 TM helix is complicated because of the
low sequence similarity and high diversity among the hydrophobicity profiles of the sequences in this region. The red and black
frames mark the final and alternative boundaries of the S1 helix,
respectively. (E) The S3 region is much less challenging in that the
various sequences manifest similar hydrophobicity profiles. The
highly conserved Asp residue, marked by a red arrow, provides
another clear signal for the alignment.
(TIF)
Figure S3 The model structure of the cytosolic domain of the
human cone channel is in agreement with experimental data. Side
view of the CNBD tetramer in cartoon representation. The
CNGA3 subunits are colored cyan (light and dark) and the
CNGB3 subunits are colored orange (light and dark). The helices
composing the C-linker, A9-F9, are marked; the helices of the
CNBD, denoted A-C, are marked in one of the subunits. The
inter-subunit interaction called ‘‘elbow on a shoulder’’ is evident:
the ‘‘elbow’’ comprises the A9 and B9 helices, which rest on the
‘‘shoulder,’’ the C9 and D9 helices of the neighboring subunit. On
the left, CNGA3 a-carbons of R436, E467 and D507 are shown as
spheres; the distance between the R436 Ca and the Ca atoms of
both E467 and D507 is 11 Å. Hence, R436 can form a salt bridge
with E467 or D507, stabilizing the intra- and inter-subunit
interface. On the right, the a-carbons of CNGA3 E467 and
CNGB3 R478 and D549 are shown as spheres; the distance
between the Ca of R436 and the a-carbons of the negatively
charged residues is 11 Å. Therefore, R478 can form a salt bridge
with E467 or D549, stabilizing the intra- or inter-subunit interface,
respectively.
(TIF)
Figure S4 Molecular interpretations for selected disease-causing
mutations. (A–D) The effects of the CNGA3 R427C mutation and
the corresponding CNGB3 Y469D mutation. In each panel,
CNBDs from two neighboring subunits are shown in side view.
The a-carbons of CNGA3 R427 and E453, as well as of CNGB3
Y469, D488, and E495, are presented as spheres. The insets show
a closer view of the residues’ interactions, marked by black
rectangles on the main panels. It is clear that CNGA3 R427 could
interact with CNGA3 E453 (A) or CNGB3 D488 and E495 (D).
Abolishment of the positive charge at position 427 by an R-to-C
mutation may disrupt the inter-subunit electrostatic interactions.
Similarly, the negative charge resulting from mutation of CNGB3
Y469 to D could result in repulsion of the mutated residue by the
negatively charged CNGA3 E453 (C) or by CNGB3 D488 and
E495 (B). The distances of the interacting residues are marked. (E)
The effect of the CNGA3 L186F mutation. A side view of the TM
region of the cone channel is presented; for clarity only one VSD is
shown. CNGA3 L186, shown as a space-filling model, is located at
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Figure S7 Mean-square displacement of the CNGA3 channel in
the holo-state according to the GNM and ANM modes. (A)
Motion I: The shape of GNM mode 1 fits the profile of ANM
mode 3. (B) Motion II: the average shape of GNM modes 2-4 fits
the profile of ANM mode 4. (C) Motion III: the average shape of
GNM modes 5 and 6 fits the profile of ANM mode 12. The
fluctuations of one chain are demonstrated, since the fluctuations
of all four chains are identical. The locations of the VSD, the pore,
the C-linker and the CNBD are marked on the x-axis. The hinge
regions are marked by arrows and the corresponding residue
numbers. The fluctuations of the channel in the apo-state
according to GNM and ANM are nearly identical (not shown).
(TIF)
Figure S8 Elastic network analysis of the CNGA3 channel
without the VSDs: Association of GNM and ANM modes. In each
panel, chain A represents an arbitrary CNGA3 chain (the channel
comprises four identical chains). (A, B) GNM mode 1 is associated
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Structure, Dynamics and Gating of a Cyclic Nucleotide-Gated Channel
with ANM mode 3. (A) Side view of the channel in cartoon
representation colored according to the correlation of the S5 helix
in chain A with the other residues in GNM mode 1. (B)
Conformations of ANM mode 3, colored according to the
direction of motion, ranging from green to red (side view). (C,
D) GNM modes 2 and 3 are associated with ANM mode 4. (C)
Side view of the channel in cartoon representation, colored
according to the correlation of the chain A S5 with the other
residues in GNM modes 2 and 3. (D) Conformations of ANM
mode 4, colored according to the direction of motion, ranging
from green to red (intracellular view). (A, C) The magnitude of
positive and negative correlations between the fluctuations of the
residues is color-coded according to the blue-to-red scale at the
bottom of the picture. Positive correlation indicates motion of two
residues in the same direction, while negative correlation indicates
motion in opposite directions.
(TIF)
overall motion of the channel. (B) Holo-state in the absence of the
VSDs. Modes 2 and 3 share the same eigenvalue. We investigated
the three slowest modes, each contributing over 3% to the overall
motion of the channel. (C) Mean-square fluctuations of the
CNGA3 tetramer in a holo-state in GNM modes 2–4. The shape
of mode 4 (red) fits the profile of the average of modes 2 and 3
(black). The fluctuations of one chain of the homotetrameric
channel are presented, since the fluctuations of the four chains are
identical.
(TIF)
Table S1 Investigation of known disease-causing mutations in
CNGA3. ConSurf grades were calculated using the ConSurf
server [40], as described in the Methods section. The ‘‘Position
occupancy in homologous proteins’’ column describes all possible
amino acids featured in the corresponding positions in homologous sequences. Positions with a ConSurf grade of less than 5 are
marked in bold. The ‘‘Effect’’ column describes the effect of the
identified the mutation on channel function: deleterious refers to
deleterious effect of the mutation on channel function; partially
deleterious includes impaired or altered function of the mutated
channel; n.d. – effect of the mutation was not determined. SF –
selectivity filter.
(PDF)
Pore-radius profiles as a function of the position along
the membrane normal. The black curve shows the profile of the
model structure of the (closed state of the) CNGA3 channel
proposed here, and the green curve shows the profile of the edge
conformation of the CNGA3 channel as predicted by the slowest
ANM mode (rotational motion I). The profiles were calculated
using the HOLE software [45]. Clearly, the pore is wider in the
‘‘rotated’’ conformation of the CNGA3 channel (green curve),
consistent with the suggestion that rotational motion I is related to
channel gating. For clarity, the pore region of two monomers is
shown in ribbon representation, colored orange and blue. As
expected, the narrowest regions in the pore correspond to the
selectivity filter and the S6 helix bundle crossing.
(TIF)
Figure S9
Investigation of disease-causing mutations in CNGB3.
ConSurf grades were calculated using the ConSurf server [40], as
described in the Methods section. The ‘‘Position occupancy in
homologous proteins’’ column describes all possible amino acids
featured in the corresponding positions in homologous sequences.
None of the mutations has been examined experimentally.
(PDF)
Table S2
Model S1 The model structure of the human cone channel
comprising of two CNGA3 and two CNGB3 subunits.
(PDB)
Figure S10 Sequence alignment of mouse HCN2, CNGA3 and
CNGB3 channels in the cytosolic region. The structural elements,
a-helices (red lines) and b-sheets (blue arrows), are marked. The ahelices are labeled with capital letters; the b-sheets are numbered
[21].
(TIF)
Acknowledgments
We thank Jens Kruger and Oliver Kohlbacher for helpful discussions and
valuable comments on the manuscript.
(A, B) The contribution of the 30 slowest GNM
modes to the overall motion of the CNGA3 tetramer. The
percentage of contribution was estimated as the weight of the
frequency of a specific mode n, calculated considering the
frequencies of all N modes (100ln/SlN). (A) Holo-state. Modes
2 and 3 share the same eigenvalue, as do modes 5 and 6. We
studied here the 6 slowest modes, each contributing over 4% to the
Figure S11
Author Contributions
Conceived and designed the experiments: YG CS DSM TH NBT.
Performed the experiments: YG CS DSM TH. Analyzed the data: YG CS
DSM TH NBT. Contributed reagents/materials/analysis tools: TH DSM.
Wrote the paper: YG CS DSM TH NBT.
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